Evidence map›Paper›PMID 38598140›Full record

ArticleInternational journal of computer assisted radiology and surgery2024

Enhancing robotic telesurgery with sensorless haptic feedback.

Nural Yilmaz, Brendan Burkhart, Anton Deguet, Peter Kazanzides, Ugur Tumerdem

Abstract read
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In one paragraph

Article in International journal of computer assisted radiology and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Nural YilmazDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA. nyilmaz2@jhu.edu.ORCID http://orcid.org/0000-0002-1421-0127
Brendan BurkhartDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA.ORCID https://orcid.org/0009-0005-4711-0279
Anton DeguetDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA.ORCID https://orcid.org/0000-0003-3856-2095
Peter KazanzidesDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA.ORCID https://orcid.org/0000-0002-6117-5467
Ugur TumerdemDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, 21218, USA.ORCID https://orcid.org/0000-0002-5322-2366

Funding

National Science Foundation 1927354The Scientific Research Department (BAP, Marmara University) FDK-2022-10751
6 · The paper itself

Abstract

purposeThis paper evaluates user performance in telesurgical tasks with the da Vinci Research Kit (dVRK), comparing unilateral teleoperation, bilateral teleoperation with force sensors and sensorless force estimation.

methodsA four-channel teleoperation system with disturbance observers and sensorless force estimation with learning-based dynamic compensation was developed. Palpation experiments were conducted with 12 users who tried to locate tumors hidden in tissue phantoms with their fingers or through handheld or teleoperated laparoscopic instruments with visual, force sensor, or sensorless force estimation feedback. In a peg transfer experiment with 10 users, the contribution of sensorless haptic feedback with/without learning-based dynamic compensation was assessed using NASA TLX surveys, measured free motion speeds and forces, environment interaction forces as well as experiment completion times.

resultsThe first study showed a 30% increase in accuracy in detecting tumors with sensorless haptic feedback over visual feedback with only a 5-10% drop in accuracy when compared with sensor feedback or direct instrument contact. The second study showed that sensorless feedback can help reduce interaction forces due to incidental contacts by about 3 times compared with unilateral teleoperation. The cost is an increase in free motion forces and physical effort. We show that it is possible to improve this with dynamic compensation.

conclusionWe demonstrate the benefits of sensorless haptic feedback in teleoperated surgery systems, especially with dynamic compensation, and that it can improve surgical performance without hardware modifications.

Indexed as

Robotic Surgical ProceduresEquipment DesignFeedbackHumansLaparoscopyPalpationPhantoms, ImagingRoboticsTelemedicineUser-Computer InterfaceDeep learningForce sensingHapticsTeleoperation

Identifiers

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.